Huawei Canada has an immediate permanent opening for a Senior Researcher.
About the team:
The Human-Machine Interaction Lab unites global talents to redefine the relationship between humans and technology. Focused on innovation and user-centered design, the lab strives to advance human-computer interaction research. Our team includes researchers, engineers, and designers collaborating across disciplines to develop novel interactive systems, sensing technologies, wearable and IoT systems, human factors, computer vision, and multimodal interfaces. Through high-impact products and cutting-edge research, we aim to enhance user experiences and interactions with technology.
About the job:
Develop and implement acoustic/speech signal processing algorithms for a range of applications, including event detection, automatic speech recognition, beamforming and speech enhancement
Conduct research and experimentation to explore new approaches and techniques in acoustics, including deep learning, recurrent neural networks and other machine learning methods
Collaborate with cross-functional teams to design, develop, and integrate acoustic-related solutions into products and systems
Evaluate and validate the performance of acoustic-related algorithms using quantitative and qualitative metrics
Develop effective techniques and infrastructure from the idea to the running prototype
Stay up-to-date with the latest research in acoustics, conversational AI, machine learning, and related fields, as well as incorporate new techniques and approaches into research projects
About the ideal candidate:
Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on acoustics, speech processing and machine learning
Proficiency in Python and at least one of the following languages: Java, C++, or JavaScript
Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
Familiarity with audio/speech processing techniques and libraries such as PyAudio, Librosa, or TorchAudio
Background in machine learning techniques with large amounts of noisy data
Relevant research experience (publications at NeurIPS, ICML, ICLR, InterSpeech, AES, ICASSP, or similar)
Strong analytical skills and a solid understanding of digital signal processing, statistical signal/speech processing and spectral/spatial filtering
Experience solving complex problems and comparing alternative solutions, tradeoffs and diverse points of view to provide one or a set of optimal solutions
